In an LTE system, a Multi-Input Multi-Output (MIMO) technology and a Precoding technology are adopted to increase system capacity. Specifically, one or more layers of data is precoded and then transmitted by using a multi-antenna configuration on a transmitting end. According to different channel conditions, the transmitting end may automatically adjust the number of layers of the transmitted data and a precoding matrix, so as to achieve the objective of increasing the system capacity.
At a transmitting end, downlink channel status information that includes Rank Indication (RI) and a Precoding Matrix Indicator (PMI) may be specifically known through feedback from a receiving end. The RI is used to adjust the number of layers of data at the transmitting end. The PMI is an index in a codebook set of the precoding matrix known at the transmitting end and the receiving end, and is used to adjust the precoding matrix that is used at the transmitting end. It is specified in an LTE protocol that, in a single antenna port or a transmit diversity transmission mode, RI=1, and no PMI exists; and in a space multiplexing transmission mode, the receiving end needs to feed back a corresponding RI and PMI.
In an MIMO precoding model of the LTE system, a process of the receiving end determining the corresponding RI and PMI may specifically include: first calculating Signal to Interference plus Noise Ratios (SINRs) of all layers and all precoding matrices at each sub-carrier, and then calculating an approximate maximum value of a throughput of the system according to the obtained SINR, and finally using an RI and a PMI corresponding to the approximate maximum value of the throughput as the RI and PMI that are required to be fed back by the receiving end to the transmitting end.
A process for determining the SINR by calculation in the prior art is described in the following.
A model of receiving a signal at a sub-carrier in the LTE system is: y=HWx+n, where W is a precoding matrix having a dimensionality of NT×ν, ν is the number of layers, and H is a channel transmission matrix of NR×NT.
Correspondingly, at the receiving end, a SINR of a kth (k=1, 2, . . . , ν) symbol may be determined specifically by using a Minimum Mean Square Error (MMSE) algorithm:
                    SINR        k            ⁡              (                  v          ,          W                )              =                  1                                            σ              2                        ⁡                          (                                                                    σ                    2                                    ⁢                                      I                    v                                                  +                                                      W                    H                                    ⁢                                      H                    H                                    ⁢                  HW                                            )                                kk                      -            1                              -      1        ;
where (σ2Iν+WHHHHW)kk−1 represents a kth diagonal element of a matrix (σ2Iν+WHHHHW)−1 and means a sum of power of normalized signals and power of interference.
After each SINRk (ν,W) is calculated in a codebook set of a corresponding layer, a precoding matrix and the number of layers may be selected according to a certain rule
            optimize              (                  v          ,          W                )              ⁢          f      ⁡              (                              SINR            k                    ⁡                      (                          v              ,              W                        )                          )              ,where ƒ(•) is a cost function, for example, may be a throughput. Taking as an example that a throughput is served as a cost function, an effective SINR corresponding to each codeword stream may be converted according to the obtained SINR by calculation, so as to obtain a Modulation and Code Scheme (MCS) corresponding to each codeword stream, and then an approximate throughput is calculated according to a coding rate and the MCS, which may specifically be:
  Throughput  =            ∑              i        =        1            q        ⁢                  N        i            ·              (                              M            i                    ·                      R            i                          )            
where Ni represents the number of layers to which an ith (i=1, 2, . . . , q) codeword stream is mapped, Ri represents a coding rate, and Mi represents a modulation order.
After the corresponding approximate throughput is obtained by calculation, a PMI and an RI corresponding to the approximate maximum throughput may be selected as the PMI and RI that are fed back by the receiving end.
In the implementation of the present invention, the inventor finds that the prior art has at least the following problems.
In a joint estimation algorithm of the PMI and the RI, SINR values of all layers (ν) and all precoding matrices (codebook indexes) at each sub-carrier need to be calculated. In the prior art, an inverse of a positive definite Hermite matrix needs to be calculated in a calculation process of each SINR. A corresponding process of calculating the inverse of the corresponding matrix is implemented by adopting a Cholesky decomposition manner, and the calculation amount for calculating an inverse of each matrix has a cubic magnitude of a matrix order ν (ν=1, 2, . . . , the maximum number of layers). Obviously, the calculation amount in the corresponding calculation process is quite high.